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Record W7024345965

Restructuring Training (Participation House Support Services)

2021· article· en· W7024345965 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2021
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsnot available
Fundersnot available
KeywordsRestructuringTraining (meteorology)DelegateScope (computer science)ResentmentTask (project management)Process (computing)Burnout
DOInot available

Abstract

fetched live from OpenAlex

Participation House Support Services (PHSS) is a non-profit organization with over 60 locations across Ontario that serves individuals with complex medical, physical, and developmental needs with the goal of including them in the community. The scope of the project covers members of the PHSS organization and the London community that they serve by addressing problems with burnout and culture of resentment that the Coordinators of the organization face. After initial discussions with the community partner, qualitative research was done via focus groups with PHSS Coordinators and training staff. An agreed-upon solution of restructuring the training process was developed, as training is a heavy task for Coordinators in addition to their daily patient-centered responsibilities. Currently, training occurs for one day at their Project Hope location prior to new hires entering specific PHSS locations. This has caused issues with information overload and unmatched expectations. The outcome of this project is to add an additional day of training at Project Hope so new hires are better trained and more knowledgeable before entering locations to engage in patient-centered training. Although not all training processes are feasible to delegate to Project Hope, most of the administrative tasks offloaded from the Coordinators should result in less burnout and a more positive culture for the organization. In addition, a feedback form will be created to gauge the effectiveness of the deliverable. The new training structure will be piloted for 20 new hires and additional videos will be added prior to implementing it across all 60+ PHSS locations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.076
Threshold uncertainty score0.255

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0760.016

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.082
GPT teacher head0.289
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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